A prototype for a mobile-based system of skin lesion analysis using supervised classification

Mobile Teledermatology appears nowadays as a promising tool with the potential to empower patients to adopt an active role in managing their own health status, while facilitates the early diagnosis of skin cancers. The main objective of this work is to create a mobile-based prototype to analyze skin lesions based on supervised classification. The presented self-monitoring system collects, processes and storages information of skin lesions through the automatic extraction and classification of specific visual features. The selected features are based on the ABCD rule, which considers 4 visual criteria considered highly relevant for the detection of malignant melanoma. The algorithms used to extract and classify these features are briefly described, as well as the overall system requirements and architecture.